Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	Louisiana	31,031
2	Florida	28,191
3	Arizona	27,380
4	Mississippi	26,613
5	Alabama	23,911
6	Georgia	22,780
7	New York	22,386
8	South Carolina	22,042
9	New Jersey	21,599
10	Nevada	21,594
11	Texas	21,152
12	Tennessee	20,866
13	Rhode Island	20,174
14	District of Columbia	19,389
15	Arkansas	19,011
16	Massachusetts	18,341
17	Iowa	18,258
18	Illinois	17,820
19	Maryland	17,459
20	Delaware	17,419
21	California	17,268
22	Idaho	17,149
23	Nebraska	16,738
24	Utah	15,555
25	North Carolina	15,082
26	Connecticut	14,596
27	Oklahoma	13,690
28	Indiana	13,436
29	Virginia	13,430
30	North Dakota	13,428
31	Kansas	13,417
32	Wisconsin	13,130
33	South Dakota	13,005
34	Missouri	12,733
35	Minnesota	12,545
36	New Mexico	11,701
37	Michigan	10,888
38	Pennsylvania	10,529
39	Kentucky	10,474
40	Ohio	9,966
41	Washington	9,801
42	Colorado	9,754
43	Puerto Rico	9,618
44	Alaska	7,683
45	Wyoming	6,278
46	Montana	6,221
47	Oregon	6,024
48	New Hampshire	5,258
49	West Virginia	5,242
50	Hawaii	4,916
51	Maine	3,249
52	Vermont	2,519

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Mississippi	217
2	North Dakota	215
3	Georgia	190
4	Alabama	184
5	Kansas	176
6	Louisiana	171
7	Iowa	170
8	Texas	162
9	Idaho	156
10	Indiana	155
11	Tennessee	153
12	Missouri	149
13	Hawaii	147
14	Nevada	147
15	California	143
16	South Carolina	141
17	Illinois	140
18	South Dakota	139
19	North Carolina	134
20	Oklahoma	132
21	Arkansas	129
22	Florida	122
23	Puerto Rico	119
24	Kentucky	117
25	Rhode Island	110
26	Minnesota	108
27	Nebraska	103
28	Virginia	100
29	Wisconsin	98
30	Utah	95
31	Michigan	86
32	Maryland	83
33	Montana	80
34	Colorado	71
35	District of Columbia	70
36	Ohio	66
37	Arizona	63
38	Alaska	58
39	Washington	56
40	Oregon	55
41	Wyoming	52
42	Massachusetts	51
43	Connecticut	48
44	Delaware	45
45	Pennsylvania	42
46	West Virginia	39
47	New Mexico	37
48	New York	27
49	New Jersey	25
50	New Hampshire	14
51	Maine	12
52	Vermont	10

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	1,796
2	New York	1,670
3	Massachusetts	1,300
4	Connecticut	1,251
5	Louisiana	1,031
6	Rhode Island	980
7	District of Columbia	855
8	Mississippi	777
9	Michigan	669
10	Arizona	658
11	Illinois	643
12	Delaware	619
13	Maryland	613
14	Pennsylvania	598
15	Florida	492
16	South Carolina	491
17	Georgia	484
18	Indiana	481
19	Alabama	415
20	Texas	414
21	Nevada	399
22	New Mexico	357
23	Ohio	341
24	Colorado	335
25	Iowa	335
26	Minnesota	323
27	New Hampshire	315
28	California	314
29	Virginia	292
30	Washington	257
31	Missouri	252
32	North Carolina	248
33	Arkansas	235
34	Tennessee	235
35	Kentucky	205
36	Nebraska	199
37	Wisconsin	189
38	Oklahoma	188
39	North Dakota	186
40	Idaho	183
41	South Dakota	181
42	Kansas	148
43	Utah	124
44	Puerto Rico	123
45	West Virginia	104
46	Oregon	103
47	Maine	97
48	Vermont	92
49	Montana	90
50	Wyoming	63
51	Alaska	45
52	Hawaii	33

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Mississippi	8
2	Louisiana	7
3	Georgia	5
4	Arkansas	4
5	Florida	4
6	Texas	4
7	Idaho	3
8	Nevada	3
9	Tennessee	3
10	California	2
11	Iowa	2
12	Montana	2
13	Rhode Island	2
14	South Carolina	2
15	West Virginia	2
16	Alabama	1
17	Alaska	1
18	Arizona	1
19	Delaware	1
20	Illinois	1
21	Indiana	1
22	Kentucky	1
23	Maryland	1
24	Massachusetts	1
25	Michigan	1
26	Minnesota	1
27	Missouri	1
28	New Mexico	1
29	North Carolina	1
30	North Dakota	1
31	Oklahoma	1
32	Oregon	1
33	Puerto Rico	1
34	Utah	1
35	Virginia	1
36	Colorado	0
37	Connecticut	0
38	District of Columbia	0
39	Hawaii	0
40	Kansas	0
41	Maine	0
42	Nebraska	0
43	New Hampshire	0
44	New Jersey	0
45	New York	0
46	Ohio	0
47	Pennsylvania	0
48	South Dakota	0
49	Vermont	0
50	Washington	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	141,085	1	99
Lafayette	Florida	138,209	2	99
Lake	Tennessee	116,876	3	99
Lee	Arkansas	112,115	4	99
Lincoln	Arkansas	106,265	5	99
Davidson	Tennessee	36,569	153	95
Richland	South Carolina	24,254	407	87
Orange	California	14,687	972	69
York	South Carolina	14,410	996	68
Pierce	Washington	8,028	1771	43

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	4,612	1	99
Galax city	Virginia	4,412	2	99
Randolph	Georgia	3,983	3	99
Terrell	Georgia	3,634	4	99
Neshoba	Mississippi	3,400	5	99
Richland	South Carolina	450	671	78
Davidson	Tennessee	359	848	73
Orange	California	287	1026	67
Pierce	Washington	194	1341	57
York	South Carolina	139	1597	49

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.